Q_all_memory

beast.fitting.fit.Q_all_memory(prev_result, obs, sedgrid, obsmodel, qnames_in, p=[16.0, 50.0, 84.0], gridbackend='cache', max_nbins=200, stats_outname=None, pdf1d_outname=None, pdf2d_outname=None, pdf2d_param_list=None, grid_info_dict=None, lnp_outname=None, lnp_npts=None, save_every_npts=None, threshold=-40, resume=False, use_full_cov_matrix=True, do_not_normalize=False)[source]

Fit each star, calculate various fit statistics, and output them to files. All done in one function for speed and ability to resume partially completed runs.

Parameters:

  • prev_result (dict) – previous results to include in the output summary table usually basic data on each source

  • obs (Observation object instance) – observation catalog

  • sedgrid (str or grid.SEDgrid instance) – model grid

  • obsmodel (beast noisemodel instance) – noise model data

  • qnames (list) – names of quantities

  • p (array-like) – list of percentile values

  • gridbackend (str or grid.GridBackend) – backend to use to load the grid if necessary (memory, cache, hdf) (see beast.core.grid)

  • max_nbins (int (default=200)) – maxiumum number of bins to use for the 1D likelihood calculations

  • save_every_npts (int) – set to save the files below (if set) every n stars a requirement for recovering from partially complete runs

  • resume (bool) – set to designate this run is resuming a partially complete run

  • use_full_cov_matrix (bool) – set to use the full covariance matrix if it is present in the noise model file

  • stats_outname (str) – set to output the stats file into a FITS file with extensions

  • pdf1d_outname (str) – set to output the 1D PDFs into a FITS file with extensions

  • pdf2d_outname (str) – set to output the 2D PDFs into a FITS file with extensions

  • pdf2d_param_list (list of strs or None) – set to the parameters for which to make the 2D PDFs

  • grid_info_dict (dict) – Set to override the mins/maxes of the 1dpdfs, and the number of unique values

  • lnp_outname (str) – set to output the sparse likelihoods into a (usually HDF5) file

  • threshold (float) – value above which to use/save for the lnps (defines the sparse likelihood)

  • lnp_npts (int) – set to a number to output a random sampling of the lnp points above the threshold. Otherwise, the full sparse likelihood is output.

  • do_not_normalize (bool) – Do not normalize the prior weights before applying them. This should have no effect on the final outcome when using only a single grid, but is essential when using the subgridding approach.

Return type:

N/A